[1]} used a tree LSTM network along the shortest dependency path (SDP) between two entities to find the relation between them. They used a bottom-up tree LSTM and top-down tree LSTM in their model. In the bottom-up tree LSTM, each node receives information from all of its children. The hidden representation of the root node of this bottom-up tree LSTM is used as the final output. In the top-down tree LSTM, each node receives the information from its parent node. The hidden representations of the head token of two entities are the final output of this tree LSTM. The representations of the bottom-up tree LSTM and top-down tree LSTM are concatenated and passed to a classifier to find the relation. They showed that using the SDP tree over the full dependency tree is helpful as unimportant tokens for the relation are ignored in the process.
